Robohub.org
 

Using 3D snapshots to control a small helicopter


by
30 September 2012



share this:

In the latest article in the Autonomous Robots journal, researchers from the Australian Defense Force Academy present a new control strategy for small flying robots that uses only vision and inertial sensors.

To control a flying robot, you usually need to know the attitude of the robot (roll, pitch, yaw), where it is in the horizontal plane (x,y), and how high it is from the ground (z). While attitude measurements are provided by inertial sensors on board the robot, most flying robots rely on GPS and additional range sensors such as ultra-sound sensors, lasers or radars to determine their position and altitude. GPS signal however is not always available in cluttered environments and can be jammed. Additional sensors increase the weight that needs to be carried by the robot. Instead Garratt et al. propose to replace position sensors with a single small, low cost camera.

By comparing a snapshot taken from a downward pointing camera and a reference snapshot taken at an earlier time, the robot is able to calculate its displacement in the horizontal plane. The loom of the image is used to calculate the change in altitude. Image loom corresponds to image expansion or contraction as can be seen in the images below. By reacting to these image displacements, the robot is able to control its position.

Grass as seen from altitudes of 0.25 m, 0.5 m, 1.0 m and 2.0 m (from left to right).

Using this strategy, the researchers were able to show in simulation that a helicopter could perform take-off, hover and the transition from low speed forward flight to hover. The ability to track horizontal and vertical displacements using 3D snapshots from a single camera was then confirmed in reality using a Vario XLC gas-turbine helicopter.

In the future, the authors intend to further test the 3D snapshot control strategy in flight using their Vario XLC helicopter before moving to smaller platforms such as an Asctec Pelican quadrotor. Additional challenges include taking into account the shadow of the robot, which might change position from snapshot to snapshot.

Source: Matthew A. Garratt, Andrew J. Lambert and Hamid Teimoori (2012) Design of a 3D snapshot based visual flight control system using a single camera in hover, Autonomous Robots.




Sabine Hauert is President of Robohub and Associate Professor at the Bristol Robotics Laboratory
Sabine Hauert is President of Robohub and Associate Professor at the Bristol Robotics Laboratory

            AUAI is supported by:



Subscribe to Robohub newsletter on substack



Related posts :

AI brings object-level vision prosthetics closer to reality

  23 Jun 2026
Researchers are developing AI models that could one day enable vision prosthetics able to restore meaningful, object-level sight for the blind.

AURA Foresight Reaches Global XPRIZE Wildfire Finals in Alaska

  19 Jun 2026
One of only four teams remaining from more than 130 competitors worldwide, our team AURA Foresight is developing autonomous technology to stop wildfires before they grow out of control. AURA Foresi...

Robot Talk Episode 161 – Collaborative haptic systems, with Allison Okamura

  19 Jun 2026
In the latest episode of the Robot Talk podcast, Claire chatted to Allison Okamura from Stanford University about developing advanced robotic systems for haptic (touch) interaction.

New research enables a robot to chart a better course

  17 Jun 2026
By rapidly generating a smooth path plan that cuts travel time and avoids obstacles, the open-source “MIGHTY” system could streamline disaster recovery and parcel delivery.

Entangled robotic matter with cohesive motion

  15 Jun 2026
Engineers have developed a robotic collective that behaves less like a machine and more like a material that flows.

Robot Talk Episode 160 – Robotic blacksmiths, with Edward Mehr

  12 Jun 2026
In the latest episode of the Robot Talk podcast, Claire chatted to Edward Mehr from Machina Labs about their RoboCraftsman that shapes complex metal parts for the aerospace, defence, and automotive industries.

Congratulations to the #AAMAS2026 best paper award winners

  08 Jun 2026
Find out who won in the categories of best paper, best student paper, and best blue sky paper.

Robot Talk Episode 159 – Robot sensing and manipulation, with Maria Koskinopoulou

  05 Jun 2026
In the latest episode of the Robot Talk podcast, Claire chatted to Maria Koskinopoulou from Heriot-Watt University about autonomous robotic manipulators for surgery, industry, and beyond.



AUAI is supported by:







Subscribe to Robohub newsletter on substack




 















©2026.05 - Association for the Understanding of Artificial Intelligence